class_docstr: This class is a child class of the ComprehensiveFCParameters class
  and has the same functionality as its base class. The only difference is,
  that most of the feature calculators are disabled and only a small
  subset of calculators will be calculated at all. Those are denoted by an attribute called "minimal".
  
  Use this class for quick tests of your setup before calculating all
  features which could take some time depending of your data set size.
  
  You should use this object when calling the extract function, like so:
  
  >>> from tsfresh.feature_extraction import extract_features, MinimalFCParameters
  >>> extract_features(df, default_fc_parameters=MinimalFCParameters())
code: def __init__(self):
      ComprehensiveFCParameters.__init__(self)
  
      for fname, f in feature_calculators.__dict__.items():
          if fname in self and (
              not hasattr(f, "minimal") or not getattr(f, "minimal")
          ):
              del self[fname]
  
imports: import logging
  from builtins import range
  from collections import UserDict
  from inspect import getfullargspec
  from itertools import product
  import cloudpickle
  import pandas
  from tsfresh.feature_extraction import feature_calculators
  from tsfresh.utilities.string_manipulation import get_config_from_string
label_desc: Use image node_id 1 to create a new MinimalFCParameters object from inherited base classes: ComprehensiveFCParameters with example: obj = MinimalFCParameters()